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Institute for Cyber Security. On Data Provenance in Group-centric Secure Collaboration. Oct. 17, 2011 CollaborateCom Jaehong Park, Dang Nguyen and Ravi Sandhu Institute for Cyber Security University of Texas at San Antonio. Group-centric Collaboration. Group Collaboration Operations.

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On data provenance in group centric secure collaboration

Institute for Cyber Security

On Data Provenance in Group-centric Secure Collaboration

Oct. 17, 2011


Jaehong Park, Dang Nguyen and Ravi Sandhu

Institute for Cyber Security

University of Texas at San Antonio

Group collaboration operations
Group Collaboration Operations

  • Administrative operations

    • Establish/disband groups, join/leave/substitute users, add/remove object versions to/from a group, import/merge object versions from a group to an org

  • Usage operations

    • Read/update/create object versions

Towards assured data provenance
Towards Assured Data Provenance

Data Provenance Security & Trustworthiness

e.g. Provenance Access/Usage Control

Some Assurance

Provenance Data

Data Provenance Model/System

GC Provenance

Operations for Provenance

Some Utilities

Target Domain

Group Collaboration

Data provenance
Data Provenance

  • Utilities of data provenance

    • Pedigree, Usage tracking, Versioning capability

    • Trustworthiness, Accountability, Compliance

    • Depend on the kinds of provenance data that are captured

Capturing provenance data
Capturing Provenance Data

  • Capturing a complete provenance data for all operations is neither feasible nor necessary

    • Some can be captured only by user’s manual declaration (i.e., user intention) while user’s memory is limited and cannot identify all the source information (i.e., citations in scientific research article).

    • Not all operation information provide additional provenance utilities

  • For proper discussion, we need a specific application domain where a set of operations can be specified and expressed

Data provenance requirements
Data Provenance Requirements




  • Identifying operations for provenance data

  • Capturing operations as provenance data in a provenance model

  • Provenance data expression

  • Provenance data querying

  • Provenance data analysis

  • Data Provenance Assurance

    • Access/usage Control, trustworthiness, integrity, accountability, etc.

Data object versioning
Data Object Versioning

One object can have multiple versions

Each version can have a multiple identical copies

The versions of an object form a rooted tree structure, relating a parent version to its immediate children versions

Each copy is considered as a separate object.

Open provenance model opm notations
Open Provenance Model (OPM) Notations

  • 3 Nodes

    • Artifact (ellipse)

    • Process (Rectangle)

    • Agent (Octagon)

  • 5 Causality dependency edges (not dataflow)

Opm includes
OPM includes…

  • A unique identifier for each node

    • To distinguish nodes of the same type

  • Accounts

    • Multiple abstracted views of provenance graph by utilizing indirect (dashed) edges

  • OPM Profile

    • Includes domain specific subtypes of edges that are defined for additional semantics

    • Includes role-specific (solid) edges

Merge operation
Merge Operation

  • Similar to “import”

    • A version is copied from cg to org

  • Different from “import”

    • The initial version of the merged version in cg was added from the org while the initial version of imported version is newly created in cg

    • The merged version becomes a new version of the original version in org

Opm in rdf expression
OPM in RDF Expression

Using RDF (Resource Description Framework) data representation to express provenance data

RDF supports a directed graph






Opm profile for group collaboration operations subtypes of wasderivedfrom
OPM Profile for Group Collaboration Operations (subtypes of “wasDerivedFrom”)










Roles for used edges
Roles for “ “Used” Edges
















Roles for wasgeneratedby edges
Roles for “ “WasGeneratedBy” Edges










Sparql query expression
SPARQL Query Expression

Standard query language for RDF

Can query by stating a consecutive path of specific triple types of subject, predicate, and object



gcp:cg1.o2v2 gcp:wasCopyOf ?obj.

?objgcp:wasNewVersionOf ?ver.}

Gleen enabled sparql

Gleen is a plugin for the ARQ query engine.

ARQ is a query engine for Jena, a semantic web framework for Java which supports the SPARQL RDF query language

GleenonPath function supports regular expression-based recursive path patterns

subject gleen:OnPath (pathExpression object)

Sample query 1
Sample Query 1

Identify the very initial version of cg1.o2v3 and whether it is created in the current group or added from an organization.

The query will return “cg1.o2v1” and “add”

SELECT ?obj ?proc


gcp:cg1.o2v3 gleen:OnPath(

”[gcp:wasNewVersionOf]∗” ?obj ).


[gcp:g(toCreate)]|[gcp:g(toAdd)] ?proc).}

Sample query cont
Sample Query (cont.)

To verify users who may have influenced (update/create) an object content regardless of the fact that whether the influence is done on a version of the same object or a version of a copied object of the object.

SELECT ?agent


gcp:org1.o1v4 gleen:OnPath(

”([ gcp:wasNewVersionOf ]|[gcp:wasCopyOf])∗” ?obj).

?objgleen:OnPath([gcp:g(toUpdate )]|[gcp:g(toCreate)] ?proc).

?proc gcp:wasControlledBy ?agent.}


Identified/captured available or necessary operations as provenance data for group collaboration environment

Expressed in RDF triples so it can be queried by utilizing a regular expression based path patterns in SPARQL query language

Showed some utilities of data provenance in a group collaboration environment

Provides an initial foundation for data provenance access control in group collaboration environment